Personal Informatics in Practice: Deep Personalization

Bon Adriel Aseniero is currently a computer science undergraduate researcher at the University of Calgary under the supervision of Dr. Sheelagh Carpendale and Dr. Anthony Tang. He has an interest in Art and Aesthetic Design, while his research is mainly in Personal Informatics and Visual Analytics.

I have used some applications in my phone that keep track of my activities. Most of them do a good job in their own right; however, they always seem to come out short –no single application tracks my activities in the way I really want it to be tracked, and the feedback is almost always some graphs which are either unappealing or doesn’t give room for self-discovery. I can’t play with my data.

From the above anecdote, we can agree that users of personal informatics tools are not just members of a generalized population but also individuals. As such, they have their own goals and reasons on why they use the tools, and use a variety of reflection methods, some of which may be unique to the individual. While it is true that these goals and reflection methods may be similar enough that they can be addressed by a generalized one-size-fits-all type of personal informatics tool, but I just can’t let go of the fact that some of their needs may not be met fully. Moreover, the feedback mechanism lacks participation from the individual –what you see is what you get (WYSIWYG); there is little room for an individual to experiment on his or her data to answer questions beginning with “why” or “what if”.

So if Personal Informatics is all about Personal Data, why not make the tools for reflection personalized as well?

As a possible way of supporting the above question, I propose Deep Personalization which is the process of allowing individuals to create, or to customize to a certain extent visualizations that represent and or integrate their data. In addition to the ability to have more meaningful visualizations as a result, I argue that the process of tailoring and customizing different visualizations as an activity that in of itself provides considerable insight to individuals.

This idea stems from the time when I created three different visualizations of different aspects of my life which I found interesting, and their integration. The first visualization is Activity River, which shows a stream representing my activities throughout a day. The second visualization is D’Ripples or Directional Ripples, which shows ripples representing the directions I’ve looked at through the day and the things I see in those directions. Lastly, Place Well is a visualization of the places I went to in a day. Integrating all of these visualizations is Hours, in which I took the visual aspects I deemed important in the previous three visualizations and combined them into a new interactive visualization. The design process of each visualizations required several sketches which provided me with a wealth of insight that is generally not accounted for by pre-created visualizations. Not only did it ensure that the resulting visualization visualizes my data correctly, but it also allowed me to find personally meaningful representations of my data. Furthermore, being able to participate in the feedback mechanism allowed me to uncover correlations that I may not have seen with current WYSIWYG feedback tools. It is almost like when we learn new things e.g. cooking; it is better to actually try to perform or participate in the act of cooking rather than to just look at someone else do it.

However, even though the rewards of Deep Personalization may prove really beneficial to the individual, it faces a big challenge. Much like cooking, not everyone who tries to do it on their own actually ends up cooking something great, some fails at cooking while some excels. Creating visualizations is not a trivial task. Some questions we as a community should try to address could be “to what extent should the individual be able to customize the visualizations or any other tools for reflection?”, “What type of tool should we provide for Deep Personalization? A tool as extensively freehand as Photoshop, or a more restrictive tool that gives the individual a set of building blocks to play with?” Nevertheless, there is a philosophical benefit that can rise from Deep Personalization and it all lies in finding an effective method for providing its support in our current Personal Informatics tools.

This article is a summary of a position paper by Bon Adriel Aseniero and his colleagues that was discussed at the Personal Informatics in Practice workshop at CHI 2012 in Austin, TX on May 6, 2012. The workshop was a gathering of researchers, designers, and practitioners exploring how to better support personal informatics in people’s everyday lives.

3 Responses to Personal Informatics in Practice: Deep Personalization

There is an Android App, Activity Classifier that stores its findings in Google Fusion Tables. In Fusion Tables you can look at the data lots of different ways without programming and lots more if you are prepared to try coding. This blog postshows various ways of visualising live activity data.

great research, and I like the approach you took to it. solving a palpable problem although I don’t really see anything innovative in the output. also the video demonstration is interesting and the visuals nice, but that music makes it almost totally unbearable to watch through. did you take it all from crappy 90′s movies? I realize this has nothing to do with the content of your research, but as someone who is specializing in data visualization I’m sure you are aware of the importance of delivering your data in a pleasing and easily digestible way.

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